In a contact center environment, much or little may be known about a consumer (also referred to as a customer or contact in other contact center literature) with whom the contact center may come in contact. Some businesses with contact centers deem it a competitive advantage to match personality characteristics between a consumer and a contact center agent. This anticipated compatibility is thought to increase the likelihood of increased sales, faster problem resolution, or higher customer loyalty.
The choice of characteristic or attribute upon which this compatibility is based may vary widely between businesses, countries or cultures. For many companies, it is the native language spoken. Other companies may prefer a gender match. Yet other companies may prefer something else. Given a choice, many companies might assign multiple attributes to compute this compatibility, with fine control over weights or other combinations.
Contact center solutions provided by various vendors may provide some measure of compatibility between the consumer and the available pool of contact center agents, but the data available for the computations within the contact center servers may not include data from databases held by the business (especially true in the case of cloud-hosted call centers), or that data may have to be provided statically in periodic data batches. Additionally, the control or methodology of the compatibility computation may not be configurable, dynamically or otherwise, by the business. As to the attributes themselves, currently there are often undesirable tradeoffs between binary attributes versus numerical attributes.
Accordingly, a need exists for improved methods and systems for determining the compatibility between customers and agents, and routing such customers to such agents.